The present invention relates to a method and control device for controlling a process in a controlled system wherein, at the start of each process sequence, a pre-setting of the system takes place as a function of a precalculated process parameter which exhibits a dependence on faulty input variables, where the dependence is inherent in the system.
In German Patent No. DE-A-41 31 765, the disclosure of which is hereby incorporated by reference in its entirety, a method and control device for controlling a process in an industrial plant, for instance a mill train, is shown. The actual control variable, namely the thickness of the rolling stock emerging from the plant cannot be measured in the roll gap (nip), but can be detected only indirectly as a function of the manipulated variable, in this case the positioning in the corresponding roll stand, and one or more process parameters (e.g, the rolling force). During the process sequence, the rolling force can be measured so that the actual value of the manipulated variable can be calculated at any time and thus can be fed to the control for generating the manipulated variable. In the initial phase of each process sequence (i.e. at the start of each individual rolling process) the control, however, must first go through a building up process which leads to defective thicknesses in the initial region of the rolling stock. To minimize this build-up phase of the control and thus minimize the possibility that the initial region of the rolling stock has a defective thickness, prior to the entrance of the rolling stock into the mill train, a pre-setting of the manipulated variables takes place in this method as a function of a setpoint value for the control variable (rolling stock thickness) and a precalculated value for the process parameter (rolling force). The precalculation of the rolling force takes place in this connection with a mathematical model which simulates the interdependence between the rolling force and the input variables influencing it such as, for instance, width, thickness and temperature of the rolling stock. Estimates are used for the input variables to the extent that any measured values are not yet available. As soon as the rolling stock has entered the mill train, measurements are taken of the rolling force and of the input variables. The measured values obtained are processed (e.g., statistically within the scope of a recalculation), and are then used for adapting the model, while using a neural network, to the recalculated variables (i.e., to the actual condition of the process).
Despite the adapting of the model of the process, the quality of the calculation of the rolling force, however, depends above all on the quality of the model assumptions. These model assumptions, as a rule, are arrived at with difficulty and can be greatly subject to errors. Therefore, there is a need for a method for the presetting of a controlled process which is not dependent on the establishing of model assumptions.